Joint Navigation and Multitarget Tracking in Networks

Situational-awareness provided by navigation and multitarget tracking (MTT) will change services and applications for modern convenience, public safety, and the military. This paper presents a Bayesian method for joint navigation and MTT in mobile agent networks, where the joint inference is performed through a factor graph formulation. Performing the sum-product algorithm (SPA) on the presented joint factor graph enables a probabilistic information transfer between the navigation and MTT stages that can improve the performance of both stages. Simulation results demonstrate significant improvements in navigation and MTT accuracy compared to an approach where navigation and MTT are formulated and solved as separate inference problems.

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